The class immerses students in real-world problems, and Korpi has given three students a difﬁcult task. They must use a small number of ﬁnancial instruments to hedge a larger portfolio against market risks, like rising federal interest rates, changes in bond yields and other factors. Using mathematical models and savvy computation, the students aim to reduce the risk of more complex securities into simpler, more liquid, basic trades. To do so, they must use the fewest instruments at their disposal and conduct minimal trading.

"A company has a huge portfolio with lots of different instruments that it can use to hedge with," explains Dave Heath, former Orion Hoch Chair of Mathematical Sciences who recently retired. "The question is how can you do this in an efﬁcient way? You don't want to have any time when your portfolio is exposed to loss."

The students look a bit tired - it is the end of the semester - but they eagerly answer Korpi's and Heath's penetrating questions.

Life is moving quickly for Korpi, who is critiquing a student class that he participated in just two years earlier.

Computational Finance: Making an Impact

While many of us hear ﬁnancial terms bandied about in the news, most of us don't appreciate that computational mathematics inﬂuences international business operations, currency exchange rates and returns in our 401(k) funds. With business training and outstanding mathematical acumen, Korpi reﬂects a new breed of analyst needed for all these activities - and more. Astute analysts are needed by banks, insurance companies, hedge funds, money managers, mortgage servicers - any organization that has interest rate risk that needs to be hedged, according to Korpi.

Financial analysts don't operate in a vacuum. They practice their craft in an ever-changing sea of information, says Korpi.

"They need to keep track of what the Federal Reserve is doing, what other governments are doing, and even corporations." Korpi revels in this ﬂux and the mathematical permutations needed to generate swaps, options, or options on swaps, which he explains are essentially derivatives (securities whose values are derived from other cash products, such as bonds).

"It can get complicated," Korpi muses matter-of-factly.

Watching Korpi interact with the students, take phone calls from his ofﬁce and talk deftly about his work, two things are self evident. First, Korpi has learned a great deal from Heath and other faculty during his four years as a Carnegie Mellon undergraduate. Second, he is part of an enthusiastic, intelligent generation that is changing how the world works.

Shaping a Bachelors Program To Meet Market Demand

Korpi is a harbinger of things to come, according to mathematical sciences faculty at MCS. Computational ﬁnance requires a deep knowledge of mathematics, statistics and probability.

"On a daily basis, the ﬁnancial industry identiﬁes new economic sectors that require management to secure their future growth and minimize their business risk," says Steve Shreve, director of the BSCF program. "Our graduates are at the fore- front of developing mathematics-based tools for managing these risks."

Shreve has been instrumental in guiding the development of Carnegie Mellon quantitative ﬁnance programs at the bachelor's, master's and doctoral levels. In fall 2005, Carnegie Mellon launched a revamped BSCF - one of a few truly interdisciplinary degree programs nationwide.

The new curriculum is developed and coordinated by the highly ranked Department of Mathematical Sciences together with the Tepper School of Business (ranked third internationally in 2006 by the Wall Street Journal), and the Heinz School (consistently ranked in the top 10 by U.S. News and World Report magazine). The program's core is mathematics, with the Tepper School providing courses in ﬁnance and ﬁnancial engineering. The Heinz School contributes courses in communications and organizational design. Students also receive training in statistics through the College of Humanities and Social Sciences (H&SS).

Korpi, who received a bachelor's degree before the recent curriculum overhaul, knows the value of in-depth mathematical coursework and interdisciplinary training. As an undergraduate, he went the extra mile, and it paid off.

"When I came to Carnegie Mellon, I came in as a business major and changed majors about six months after I started taking classes in the Math Department. Even though I wasn't a Ph.D. or master's student, the faculty let me sit in on classes and take the tests," Korpi reﬂects. "The speaking and writing classes from the Heinz School were also very valuable. It's one thing to do all the modeling and be comfortable with the technical details, but communication is at least half, if not more, of the whole game."

This theoretical and applied training gives students a comprehensive understanding of the mathematics needed to develop models for security prices and their derivatives. The updated curriculum also provides the statistical tools to estimate the parameters of those models, the computing skills to implement them and the ﬁnancial engineering context in which students develop innovative solutions to business problems.

Careers vary but usually include pricing and trading derivatives, quantitative portfolio management, market and credit risk management, and software development related to all the above.

When Demand Transforms a Department

The growing ﬁnancial industry demands that academic departments with programs in computational ﬁnance keep up-to-date with the rapidly changing requirements of the ﬁeld themselves, says Roy Nicolaides, Alexander M. Knaster Professor and Head of the Department of Mathematical Sciences.

"Staying ahead of the game and maintaining our leadership position is hugely important to our department. We are forever evaluating our programs and adapting them to meet the changes in this rapidly moving area."

Computational ﬁnance at Carnegie Mellon wasn't developed overnight. In 1991, Shreve founded the doctoral program in mathematical ﬁnance, which currently has 12 students. Mathematical Sciences, the Tepper School of Business and H&SS launched the Master of Science in Computational Finance (MSCF) program, 12 years ago. Considered by many to be the top quantitative ﬁnance program in the country, the MSCF includes courses taught both in Pittsburgh and in New York City through a program aimed at working professionals.

But undergraduate student interest and market demand has spurred recent, dramatic changes needed to create and sustain a truly comprehensive, interdisciplinary BSCF program, Nicolaides said. Moreover, Nicolaides points out that several mathematical sciences faculty, including himself and William Hrusa, are writing much-needed curricular materials that ﬁll the void in computational ﬁnance education. In tandem with these activities, the department is hiring additional faculty to further strengthen Carnegie Mellon's status as a computational ﬁnance powerhouse.

In 2006, Shreve became the Orion Hoch Chair, continuing Carnegie Mellon's tradition of having an internationally acclaimed expert lead an internationally acclaimed program.

Assuming Risk, Assuming Responsibility

Because BSCF graduates are well prepared, they're in high demand for full-time employment and internships. In 2006, the program achieved 100 percent placement of graduating students, with several students receiving multiple offers well before graduation. The program also achieved 100 percent placement of rising seniors seeking internships. Graduates of the precursor program to the BSCF now work at Deutsche Bank, Goldman Sachs, Citigroup, UBS, Bank of America, Citadel, American Express and similar institutions.

"If you show that you are ready to take on a lot of risk and you are comfortable managing that risk and are technically and analytically strong, they will let you take on that risk," Korpi says. "So even as a ﬁrst- or second-year analyst, I am taking on a lot more risk than a lot of my peers may be as third- or fourth- year analysts. Deutsche Bank feels I am ready to take on that responsibility, so it's been given to me."